How researchers are quantifying the life-changing impact of undergraduate research for community college students.
Imagine a community college student, passionate about science but unsure of the path forward. They land a spot in a prestigious summer research program, a "Research Experience for Undergraduates" (REU). They spend weeks immersed in a real lab, tackling unanswered questions. They emerge transformed—more confident, more skilled, and ready for a STEM career.
But how do we know they were transformed? How can we move beyond a simple feeling and actually measure the impact of such an experience? This isn't just an academic exercise. For programs designed to nurture the next generation of scientists—especially those from community colleges, which serve a diverse and often underrepresented population in STEM—proving their effectiveness is crucial. This is the world of objective attainment assessment, a scientific approach to measuring the spark of discovery.
REU programs are incubators for scientific talent. For community college students, who might not have access to high-end research facilities at their home institutions, these experiences are particularly powerful. They bridge the gap between textbook learning and the messy, thrilling reality of scientific discovery.
Moving from following cookie-cutter lab protocols to designing and executing independent experiments.
Helping students see themselves not just as students, but as scientists.
Solidifying their intent to pursue a bachelor's degree and a career in a STEM field.
Connecting with mentors and peers who share their passion.
But how do we know if these goals are being met? That's where assessment comes in.
Let's take an in-depth look at a hypothetical, but representative, study conducted to assess the "REU-CC" program (a Research Experience for Undergraduates for Community College students).
Researchers used a mixed-methods approach, combining quantitative (numerical) and qualitative (descriptive) data to get a full picture. Here's their step-by-step process:
A cohort of 30 community college students was selected for the 10-week REU-CC program. On their first day, they were given:
For 10 weeks, students engaged in authentic research projects under faculty mentors. They also attended weekly workshops on ethics, graduate school, and scientific communication.
In the final week, the same students completed:
The pre- and post-survey data revealed significant growth. The tables and charts below summarize the core findings.
| Skill | Pre-Program Average | Post-Program Average | % Change |
|---|---|---|---|
| Designing an Experiment | 2.1 | 4.3 | +105% |
| Using Complex Lab Equipment | 1.8 | 4.1 | +128% |
| Data Analysis & Statistics | 2.4 | 4.0 | +67% |
| Scientific Writing | 2.5 | 4.2 | +68% |
Analysis: The dramatic increase in confidence, especially in designing experiments and using equipment, shows the program's success in moving students from passive learners to active researchers.
| Planned Path | Number of Students (Pre) | Number of Students (Post) |
|---|---|---|
| Transfer to 4-year STEM Program | 18 | 28 |
| Enter Workforce Immediately | 8 | 1 |
| Undecided | 4 | 1 |
Analysis: This shift is one of the most powerful outcomes. The program clearly solidified students' commitment to pursuing higher education and careers in STEM.
"I always felt like an imposter in my science classes. But when I finally cloned that gene myself, I realized, 'I can do this.' I belong here."
The qualitative data from interviews provided the "why" behind the numbers. This quote perfectly illustrates the growth in scientific self-identity, an objective that is difficult to measure with numbers alone.
How do researchers capture something as intangible as "scientific identity" or "research skill"? They use a toolkit of specialized "reagents"—not chemicals, but carefully designed research instruments.
| Tool | Function | What It Measures |
|---|---|---|
| Pre-/Post-Surveys | A standardized set of questions administered before and after the program. | Quantifiable change in confidence, knowledge, and attitudes. Provides clear, comparable data. |
| Scientific Self-Efficacy Scales | A specific type of survey that gauges a person's belief in their ability to succeed in scientific tasks. | The development of a "scientist" mindset and resilience in the face of experimental failure. |
| Rubric-Based Presentation Scoring | A detailed checklist used by multiple evaluators to score final research talks or posters. | Mastery of scientific communication, depth of understanding, and ability to defend one's work. |
| Semi-Structured Interviews | Conversations guided by a set of open-ended questions, allowing for unexpected insights. | The personal, narrative journey of the student. Reveals the "spark" moments that surveys can miss. |
| Tracking Studies | Long-term follow-up (1, 5, 10 years later) to see where students ultimately go. | The ultimate measure of success: sustained participation in the STEM workforce. |
The careful assessment of REU programs for community college students is far more than just paperwork for funders. It's a vital feedback loop that ensures these initiatives truly work. By using a robust combination of surveys, interviews, and long-term tracking, we can move beyond anecdotes and prove that these experiences build skills, forge identities, and open doors.
The data is clear: when given the opportunity to do real science, students from all backgrounds don't just learn about biology, chemistry, or physics—they become biologists, chemists, and physicists. By measuring this transformation scientifically, we can refine the programs that build a stronger, more diverse, and more innovative scientific community for everyone.